A Batch Process for High Dimensional Imputation


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Documentation for package ‘hdImpute’ version 0.2.1

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check_feature_na Find features with (specified amount of) missingness
check_row_na Find number of and which rows contain any missingness
feature_cor High dimensional imputation via batch processed chained random forests Build correlation matrix
flatten_mat Flatten and arrange cor matrix to be df
hdImpute Complete hdImpute process: correlation matrix, flatten, rank, create batches, impute, join
impute_batches Impute batches and return completed data frame
mad Compute variable-wise mean absolute differences (MAD) between original and imputed dataframes.